RDF Data Partitioning for Efficient SPARQL Query Processing with Spark SQL-Reference-Cited by-同舟云学术

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RDF Data Partitioning for Efficient SPARQL Query Processing with Spark SQL

Published:2023 Issue: Volume: Page:92-106
ISSN:0302-9743
Container-title:Information Integration and Web Intelligence
language:
Short-container-title:

Author:

Yamasaki Kosuke^ORCID,Amagasa Toshiyuki^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-48316-5_12

Reference14 articles.

1. https://spark.apache.org

2. SPARQL 1.1 Query Language. Tech. rep., W3C (2013). https://www.w3.org/TR/sparql11-query

3. Akhter, A., Saleem, M., Bigerl, A., Ngomo, A.C.N.: Efficient RDF knowledge graph partitioning using querying workload. K-CAP 2021 (2021)

4. Apache: spark SQL guide. https://spark.apache.org/docs/latest/sql-distributed-sql-engine-spark-sql-cli.html

5. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters (2004)

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